Andrea Lonza
Co-Founder at Lexroom
Italy
Summary
🤩
Rockstar🎓
Top SchoolAndrea Lonza is a Co-Founder and machine learning engineer with 8 years of experience specializing in NLP, Deep Reinforcement Learning and Computer Vision, blending research-grade knowledge with product-focused deployments. He authored "Reinforcement Learning Algorithms With Python," runs a popular 60-day Deep RL learning repo on GitHub with 2,500+ stars, and placed 11th worldwide in a Kaggle high-energy physics particle-tracking competition. Andrea has driven DL initiatives in industry—from few-shot food recognition for a vision-based self-checkout system to designing core computer vision algorithms—while mentoring teams to bring AI into production. Based in Italy, he combines academic rigor (AI studies at Pi School and a computer science degree) with hands-on engineering and a knack for turning advanced RL concepts into accessible learning resources.
8 years of coding experience
4 years of employment as a software developer
Machine Learning and Deep Learning, Machine Learning and Deep Learning at Online CoursesArtificial Intelligence, Artificial Intelligence at Pi SchoolHigh School Diploma, Electronic and Telecommunications, High School Diploma, Electronic and Telecommunications at I.T.I.S. A.VoltaBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Università degli Studi di Udine
Italian, English
Github Skills (9)
neural-network10
gymnasium10
openai-gym10
pytorch10
deep-learning10
python10
reinforcement-learning10
dqn9
ppp7
Programming languages (2)
Github contributions (5)
andri27-ts/Reinforcement-Learning
Aug 2018 - Apr 2020
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Role in this project:
ML Engineer
ML EngineerContributions:140 commits, 6 PRs, 130 pushes in 1 year 8 months
Contributions summary:Andrea contributed code related to Deep Reinforcement Learning, adding implementations of Q-learning for the FrozenLake environment and Atari wrappers for Atari games. They integrated neural network architectures, including a DQN, and explored techniques like dueling DQN. The user also focused on environment setup and utilized libraries such as PyTorch and Gym.
deep-learningdeep-reinforcement-learningpythonreinforcement-learningmachine-learning
andri27-ts/1-Year-MachineLearning-Journey
Oct 2018 - Feb 2020
An advanced program in Machine Learning and Deep Learning
Contributions:5 commits, 4 pushes, 1 branch in 1 year 3 months
deep-learningmachine-learningcomputer-visionnlpdeep-reinforcement-learning
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